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ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
15 years 6 months ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
ICDM
2003
IEEE
238views Data Mining» more  ICDM 2003»
15 years 6 months ago
Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques
We present Sentiment Analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents. Instead of classifying the sentiment of an entire document abou...
Jeonghee Yi, Tetsuya Nasukawa, Razvan C. Bunescu, ...
ICDM
2003
IEEE
225views Data Mining» more  ICDM 2003»
15 years 6 months ago
Combining the web content and usage mining to understand the visitor behavior in a web site
A web site is a semi structured collection of different kinds of data, whose motivation is show relevant information to visitor and by this way capture her/his attention. Understa...
Juan D. Velásquez, Hiroshi Yasuda, Terumasa...
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
15 years 6 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 6 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
Data Mining
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